[visionscaper]

I’m not using an M1 machine yet, but I think is extremely useful to be able to do some small scale experiments for testing and debugging purposes locally before starting a full-scale training job in the cloud.

Further, in general, I’m really charmed by the potential of having unified memory; the idea you can test some batch training iterations with a batch size that fills almost all 128MB is a unique capability!

Last, a large amount of unified memory allows to do inference and “prompt engineering” with very large models, locally. E.g. Using GPT-J like models (6B parameters).